The field of the invention is systems and methods for magnetic resonance imaging (“MRI”). More particularly, the invention relates to systems and methods for separating signal contributions from two or more chemical species using MRI.
Mapping of effective transverse relaxation rate, R2*, relaxivity has important applications in MRI, including blood oxygenation level dependent (“BOLD”) functional imaging; detection and tracking of superparamagnetic iron oxides (“SPIOs”); and assessment of iron content in brain, heart, pancreas, and liver. R2* maps can be obtained from relatively rapid data acquisitions, such as gradient echo, or spoiled gradient (“SPGR”) based multi-echo imaging, which is advantageous for body imaging applications where motion is an issue.
Measurements of R2* are affected by several confounding factors. For example, the presence of fat, such as triglycerides, in the tissue under examination introduces additional modulation in the acquired signal, and can lead to severe bias in R2* measurements. Furthermore, the presence of macroscopic B0 field variations introduces additional intravoxel dephasing in the acquired signal, which can lead to severe overestimation of R2*, particularly in regions with rapid B0 gradients, such as near tissue-air interfaces, or other areas with locally sharp changes in magnetic susceptibility. These confounding factors generally make R2* maps dependent on the data acquisition parameters. For instance, in the presence of fat, apparent R2* maps estimated without accounting for fat will heavily depend on the choice of echo times. In the presence of macroscopic field variations, the apparent R2* maps will also depend on the spatial resolution, particularly the largest dimension, which is usually the slice thickness.
Errors arising from the presence of fat are typically addressed by acquiring in-phase echoes. This approach largely addresses the effects of fat, although it does have several drawbacks. First, not all fat peaks are in phase with the water peak, just the main methylene peak; and second, the technique forces relatively large echo spacings, which may not be optimal for measuring large R2* values, such as in the presence of iron overload. Alternative techniques, such as spectrally selective fat suppression, or those that use spatial-spectral pulses, are sensitive to B0 field inhomogeneities that can be important in many applications, such as liver or heart imaging. Other techniques, such as short-tau inversion recovery (“STIR”) fat nulling, are effective and can be made insensitive to B0 and B1 inhomogeneities, but require the introduction of additional inversion pulses that result in a significant signal-to-noise ratio (“SNR”) loss, and has a tremendous impact on sequence efficiency, typically requiring an inversion time of 160-200 milliseconds every repetition time.
Methods for correcting macroscopic field inhomogeneities typically focus on the through-slice field variation, and often assume locally linear variations. These methods can be classified into two general categories: those that modify the acquisition to minimize field variation effects in the data, and those that correct the data by postprocessing.
Methods based on acquisitions modified to minimize field variation effects in the acquired data typically use several images obtained with higher resolution along the largest direction, which are subsequently magnitude-combined in order to prevent dephasing for increasing echo times. In one such method, two acquisitions are performed with different “mis-adjustments” of the refocusing part of the slice selection gradient. These images are subsequently combined in order to mitigate the dephasing due to macroscopic field variation. In another such method, a technique termed multi-gradient echo with magnetic susceptibility inhomogeneity compensation (“MGESIC”) is developed, where the slice refocusing gradient is varied between even and odd echoes. This method allows for faster acquisition with a single echo train. In yet another such method, a multiple-gradient-echo sequence is provided for mitigating the effects of background field gradients along the slice direction. This method is based on combining three successive gradient-echo images acquired with different slice refocusing gradients.
Methods based on correcting for macroscopic field variations by postprocessing are typically based on a multi-slice two-dimensional gradient-echo acquisition with a relatively large number of echoes. In one such method, the effects of the through-slice field gradient, Gb, are modeled by introducing an additional decay in the gradient-echo signals given by:
                              sin          ⁢                                          ⁢                      c            ⁡                          (                                                γ                  ⁢                                                                          ⁢                                      G                    b                                    ⁢                                      TEz                    0                                                  2                            )                                      ;                            (        1        )            
where γ is a gyromagnetic ratio, TE is an echo time, and z0 is slice thickness. The unknown parameter, Gz, is then fitted from the acquired multi-echo magnitude signal in an iterative procedure that alternates between updating the estimates for Gz and those for the signal amplitude, ρW, and for R2*. Rather than including the additional decay term in the signal model and fitting the data with the “complete” model, this method removes the additional decay and then fits the standard model to the corrected signal. This approach may be acceptable in the absence of noise, but it will alter the statistics of the noise so that a least-squares fitting is no longer accurate, which will be particularly relevant in cases of iron overload, where signal decays fast and later echoes contain mostly noise. Thus, while this approach shows good correction of background field gradients, it is limited in regions of very rapid, or in-plane, field variations. This approach is also limited because it results in significant noise amplification due to the need to estimate Gz from the magnitude data. Such noise amplification occurs with short data acquisitions like those typically performed for chemical-shift-based methods, such as iterative decomposition of water and fat with echo asymmetry and least-squares estimation (“IDEAL”).
In another postprocessing method, a high-resolution three-dimensional scan is used to estimate the B0 field map and to correct a lower resolution two-dimensional multi-slice, multi-echo acquisition. This method allows for accurate modeling of the background field gradients, but requires additional data acquisition.
In yet another postprocessing method, a multi-slice method for R2* mapping is used. The method uses long echo trains with “in-phase” echoes. The background field variation is considered in the slice direction only, and is fitted similarly to the method described above, but the value of Gz is initialized from an estimated field map, which is in turn obtained by linearly fitting the unwrapped phase of the acquired signal at each voxel. This method also attempts to remove the additional decay from the signal, and the corrected signal is fitted with a decaying exponential to obtain R2*. Again, this approach leads to significant distortions in the noise statistics, particularly in points where the value of the additional sinc-based decay term approaches zero. Acquiring only in-phase echoes forces the echoes to be spaced widely, resulting in poor ability to measure R2* in the presence of high iron concentrations.
In yet another postprocessing method, a technique is introduced for correcting quadratic, instead of just linear, background field variations in the through-slice direction. The acquisition used is a modified echo-planar imaging (“EPI”) sequence without the blipped gradients, with a large number of echoes, and with low spatial resolution. An initial B0 field map is obtained from an additional higher-resolution three-dimensional gradient-echo acquisition, which is repeated twice with different echo times. This initial field map is then used for the fitting to estimate the linear and quadratic coefficients of the B0 field variation.
In light of the foregoing approaches to minimizing the ill effects that fat tissue and macroscopic B0 field variations have on quantification of R2* measurements, it would be advantageous to provide a method for R2* quantification that accounts for macroscopic B0 field variations-related signal decays, mitigates susceptibility-related errors, requires only a single data acquisition, and mitigates SNR losses. Moreover, it would be advantageous to provide such a method that is independent of the data acquisition parameters and specific MRI system hardware.